Top AI & Machine Learning Jobs

Build customer-facing AI features and horizontal infrastructure to deliver trustworthy, auditable AI automation for financial accounting. Own full-stack feature development, measure and improve AI product efficacy, and make strategic product and technical decisions.

Build production AI and agentic workflows that combine physics-informed models, LLMs, VLMs, scientific data, retrieval, memory, and deterministic rules. Develop secure, durable systems with evidence-backed outputs, permissions, auditability, human approval, and recovery capabilities. Evaluate performance for task success, scientific validity, safety, latency, cost, and human intervention while partnering with product and design teams to deliver customer-facing intelligence tools for operational decision-making.

Build and deploy LLM-powered agents, skills, and platform capabilities across the company. Own the full lifecycle from design and implementation through evaluations, rollout, and ongoing improvement. Define specifications and measurable quality evaluations, partner with the Applied AI product manager, make independent product decisions, and collaborate with sales, revenue operations, editorial, and people operations to identify and automate workflows.

Develop and deploy predictive and generative AI models for personalization, forecasting, marketing automation, conversational agents, and other business applications. Perform exploratory analysis, statistical modeling, causal inference, and A/B testing. Build Python-based modeling workflows, collaborate on productionization and MLOps, develop RAG and agentic systems, and communicate insights to technical and non-technical stakeholders across the organization.

Conduct hypothesis-driven analyses across claims portfolios, develop heuristic and predictive models, build scalable software tools, and communicate insights to technical and nontechnical stakeholders. The role collaborates with customer-facing, product, design, and sales teams; mentors junior data scientists; performs rigorous experiments; and continuously deploys maintainable, tested code to improve claims outcomes.

Research Scientist responsible for RL-based post-training of large-scale video generation models. The role includes preference optimization, online RL, video reward model development, human and automated evaluation, reward-hacking safeguards, and secondary distillation of aligned models. Candidates need experience with generative modeling or post-training, reinforcement learning, diffusion or flow-matching models, PyTorch, and distributed training. Preferred experience includes visual-generation reward models, VLM-based judging, preference data collection, and video-specific temporal and physics failure modes.

Build and operate production AI agents that automate accounting workflows and help customers understand financial data. Shape agent architecture, develop customer-facing features, establish reliability practices, and own evaluations, tracing, monitoring, permissions, data access, human approvals, and failure recovery. Lead complex initiatives, make cross-team architectural decisions, mentor engineers, and balance accuracy, latency, cost, and complexity while remaining hands-on.

Embeds with enterprise clients to identify high-value business problems and independently design, build, and deploy solutions using Venn’s platform and centralized data. Partners with operations, marketing, finance, engineering, product, and client stakeholders to prioritize roadmaps, deliver AI-powered systems, manage risks, and drive measurable outcomes. Requires experience building products from 0 to 1 and deploying LLM or generative-model systems, with up to 25% client travel.

Lead strategy and execution for Binti's AI and core platform capabilities. Own roadmap, scale LLM-based tools (transcription, form pre-fill, case chat), partner with engineering and design, prototype rapidly with AI-native tools, conduct user research with social workers, and drive platform health and AI adoption metrics.

Leads enterprise AI architecture and delivers production-grade AI platforms and solutions. Designs agentic systems, RAG applications, LLM integrations, evaluations, monitoring, and lifecycle management. Partners with investment, engineering, risk, security, compliance, and business teams to build scalable, governed AI capabilities. Establishes technical standards, embeds controls for regulated environments, drives adoption, and mentors teams through technical influence.